Question 35
Scenario 4:
A professor in computational biology is designing an AI-powered assistant called BioTutor to help students understand bioinformatics concepts and computational techniques for analyzing genomic data. The assistant aims to foster critical thinking, independent learning, and hands-on problem-solving skills.
Guidelines for BioTutor:
● Engage students with exploratory and reflective questions.
● Avoid providing direct answers; instead, guide students to discover solutions themselves. ● Focus on building conceptual understanding and technical skills.
● Encourage students to apply bioinformatics tools and algorithms independently.
Based on the above data, answer the given subquestions.
Assume that BioTutor uses a RAG (Retrieval-Augmented Generation) system to assist students with bioinformatics queries. The system works as follows:
1. Bioinformatics Data Storage: Comprehensive genomic research materials (e.g., papers, notes, tutorials) are split into smaller chunks, which are vectorized using an embedding model. 2. Vector Database: The vectorized chunks are stored in a FAISS or Weaviate vector database. 3. Retriever: When a student asks a question, the system retrieves relevant content from the database based on semantic similarity to the query.
4. LLM Contextualization: The retrieved content is added as context in the assistant's prompt, enabling the LLM to generate a personalized response.
Which of the following correctly describes the process flow of a RAG-based system for BioTutor?